In the thesis “The use and experience of responsible gambling tools: An explorative analysis of user behaviour regarding a responsible gambling tool and the consequences of use” David Forsström explores different aspects of the use, experience and functions of Playscan. The thesis shows that Playscan is most commonly used by players with a higher risk level, the self-test is the most used feature and in addition, the self-test had good psychometric properties.
The study has shown that the tool has a high initial usage and a low repeated usage. Latent class analysis yielded five distinct classes of users: self-testers, multi-function users, advice users, site visitors, and non-users. Multinomial regression revealed that classes were associated with different risk levels of excessive gambling. The self-testers and multi-function users used the tool to a higher extent and were found to have a greater risk of excessive gambling than the other classes.
Professor Per Carlbring states, “The low usage of the tool is not a disappointment. As long as the right ones actually use the tool, which is exactly what we found. People with a higher risk level are using Playscan more.”
The prevention of problematic gambling is a complex issue. We at Playscan know it all too well. But in order to learn about effective prevention initiatives we use the method of validated learning for acquiring new knowledge.
By practising hypothesis-driven development for responsible gambling we see the development of new tools and services as a series of experiments to determine whether an expected outcome will be achieved – or not. With this we challenge the concept of having fixed requirements when we develop new features. Instead, the process is iterated until we reach a desirable outcome.
6 steps toward hypothesis-driven development
1. We make user research and formulate a hypothesis
Let us look at an example: In interviews with users we often ask them to describe their general attitudes toward their risk assessment. We hear players ask themselves: ok, so this is my risk assessment…but what do I do now?
(This is where we get the chance to identify what the user is expecting from us. From this it is our responsibility to design features that address the problem.)
Our hypothesis is:
We believe that if we clearly communicate the answer to the question “what do I do now?”
Will result in more players reducing their risk level.
We will know we have succeeded when we see an X% increase in risk levels.
2. We define targets and points to measure
We base the work on the products Impact Map, a document that help us drive our software development towards effect, meaning delivering the right responsible gambling initiative to the right player.
Example: X% more risk players know what to do in order to lover their risk level. This is measured with an online questionnaire; click through on recommendations and analysis of the gambling behavior.
3. We design an experiment to test the hypothesis
Best practices and research inspire us when we work on a solution. We talk it through with our experts on problematic gambling, write texts and produce real content.
4. We develop the solution
During the process of making the solution alive software developers, UX-designers and copywriters work closely together. Simply because it always gives us the best result. Then we launch it.
5. We validate the use, accept or reject the hypothesis
This is where we collect feedback from the player and can see if the solution delivers the use we expected. Did it work? Or do we need to change anything? Here we learn and iterate and make it even better.
Our most important work: we iterate!
To ensure that we are on the right course, we work in short iterations that are generally two weeks long. We build the system with small additions of user-valued functionality and evolve by adapting to user feedback. Have we stumbled on any mines? Well of course. But it’s a part of the game – we do not even expect to hit the target at the first time. For every experiment we do we always learn something new. Even if we had a great hypothesis (based on good observations or research) sometimes the results are just neutral. But this is why this method is so effective: we can quickly get a hint on what seems to work – and what’s not working.
A new research study just published in the journal International Gambling Studies showed that at-risk players who received behavioral feedback via Playscan were significantly more likely to reduce the amounts of money they deposited and wagered – compared with players who did not use Playscan.
The authors, Dr Richard Wood and Dr Michael Wohl, conducted the first study of this kind to use actual behavioral data, from 1,558 Internet players in a real-life setting.
“This is a relatively new area of investigation in the responsible gambling field, but our results suggest that such a tool can be very useful to help at-risk players keep better control over their gambling expenditure,” said Dr Richard Wood.
“The study provides empirical evidence, that helping players to better understand their gambling behavior has a sound practical application as a responsible gambling strategy,” added Dr Wohl.
The research provides valuable insight into how a well-designed player-tool, such as Playscan, can be utilized to ensure players have a more responsible gambling experience.
Playscan is thrilled to have been part of the study and to contribute to a better understanding of how to support responsible play.
The latest features from Playscan are now available to players gambling at Miljonlotteriet. The lottery has offered Playscan to their players for more than four years and by upgrading they will now supply players with a new and more detailed view of their gambling behavior.
– What I really like about Playscan 4 is that it is so much more than before, says Ludwig Alholt, CEO at Miljonlotteriet.
– The tool is essential not only for the player, but also for the Operator. It helps us understand and evaluate the impact of our overall responsible gambling initiatives.
Every week Playscan analyzes the gambling habits of 4.5 million players globally. Players appreciate the system, they reflect on their habits, perform self-tests and value the fact that it warns them if their gambling behavior changes into becoming more of a risky one. Which means they remain as a healthy player, as well as in control of their gambling habits.
Miljonlotteriet was founded 1964 and is one of the oldest lotteries in Sweden. We offer scratchcards via subscription, online and with retailers and bingo online. Our vision is to be the operator that is known for creating dreams and making reality out of them. Miljonlotteriet is owned by IOGT-NTO and together we have a dream that no one should have to grow up in a world surrounded by addiction. Since 2000, we have contributed with 1,6 million Swedish kroner to the work of IOGT-NTO. Do you want to know more? Please visit: www.miljonlotteriet.se
We use the Playscan Risk Analysis for two purposes. The original purpose is to use it as a basis for interventions and communication to at-risk players – now, we equally use it together with operators and creators of RG. By looking at levels of risk and changes herein, between groups, marketing campaigns, interventions, etc. we measure the effect of what we do. We quantify, instantaneously and at scale, our mistakes and our successes – every day and for everything we do.
Now, we know that these tools and methodologies could be put to more use out in the world.
Therefore, we’ve added an offering to our product portfolio: the standalone Playscan Risk Analysis. If you already have an RG communication platform or already established RG tools that fits your needs and strategy, and instead is looking to add RG metrics to your operations, this is what you’re looking for.
More-so: if you are not yet ready to invest in an integrated, fully-operational system: we at Playscan now offer our Risk Analysis and methodology as a service called Sustainable Gambling Management.
As the basis of it all, you will get a risk scoring for each of your players. From this seed, a multitude of knowledge sprouts:
Measure the effect of new RG efforts
When you’re launching a new initiative, you’d like to know what effect is has – both to understand the business and RG impact. By bringing in Playscan at the early stage of the project, we will help you track and quantify the results, and measure the effect of your new initiative.
Responsible Gambling KPI:s
The Playscan Risk Analysis unfolds nicely into a set of KPI:s. As an initial step, you may want to try out our metrics by looking at previous years of operation, to get a feeling both our metrics and how they benefit your operation today. When you decide to have these as recurring KPI:s, you have a head start of getting an Analysis Engine installation.
Development of your RG portfolio
If you feel like you’ve added all the tools and information you possibly could, but would like to make the most of it, Playscan AB can help you find a fruitful direction and get some early victories off the ground. We will join forces between your strategies and tools, and our day-to-day experience in reaching the at-risk player.
Reaching the right players with your RG tools
On our three-color-scale (green for low risk, yellow for at-risk, and red for high-risk), we see a big difference between green and yellow players. While the latter is not a uniform group of people, they tend to share traits and behavior that relieves us from much of the fear of annoying or even accusing the low risk players. After all, the green majority of players are those for whom the industry should focus on for a good and exciting experience.
In contrast, the yellow players are slightly different. They tend to identify as players, and gambling is a considerable part of their past-time. They often have self-imposed strategies to keep control of their gambling, and while they may never have developed severe problems from their gambling, they can relate to how it can spin out of control.
Now, the difference between green and yellow is vast: not just in terms of the operator walking the balance between business goals and compliance, but also as a divider between those who (yet, at least) don’t need and don’t want to dig deep into the plethora of tools, and those for whom it is both interesting and relevant.
We know how to communicate with increased risk players: let’s set up a strategy, reaching the right player with the right tool at the right time.
To learn more, pop us an email , catch us at one of the events we’re at or shoot us a tweet!
Phd student David Forsström presenting results from his studies at SNSUS conference and at the Department of Psychology, Stockholm University.
In the first study (to be presented at Stockholm University) user behavior was analyzed and the main finding was the identification of five distinct classes of users: Very high usage, high usage, advice users, site visitors and non-users.
The second study (to be presented at SNSUS) focuses on how the user experiences Playscan. The main findings are that users want more feed-back from the system and that the type of gambling activity online influences Playscan usage.
First study will be presented at Stockholm University at June 2, 2015
The second study will be presented at the SNSUS conference in Stockholm at June 3, 2015
To make sure you have impact, do quick experiments and redesign things based on usability principles. By doing so, we found out that displaying only one recommendation at the time makes more people click.
A click on a recommendation is a success for Playscan. It means that we’ve provoked a reaction or created interest for taking action.
Sometimes, the little stuff create a big difference. As Thaler and Sunstein writes in their bestseller Nudge: “[S]mall and apparently insignificant details can have major impacts on people’s behaviour. A good rule of thumb is to assume that “everything matters””. With the “everything matters” mindset, the insignificant details can indeed prove fruitful beyond expectation.
Back in the days, Playscan always showed two recommendations to players. The rationale was that this was a trade-off between making sure to give the player more than one choice, to make sure he could find something relevant, but not to overwhelm him with too many. From nothing but our own curiosity, we decided to test whether we were correct.
We randomly divided our visitors into three groups, presenting them with one, two or three recommendations respectively. Next, we measured the click-through rate during a two week period. At the end of it, we realized that we had left a good many clicks on the table.
Our original design with two recommendations proved a 20% click-through, measured as the proportion of players who clicked any tip. The three-tip version showed no significant difference, but our one-tip version did: 36% of players clicked the recommendation. Again: the only change was one vs two recommendations – no other design changes, the same selection of recommendation, no new content – and from this we doubled our click-through!
Hindsight is always 20/20, and there is a reasonable explanation for what we found: players are more likely to click through with fewer conflicting and maybe confusing recommendations to choose from. Still, before our test we thought we had an equally good theory of why two recommendations was the way to do things.
So while doubling our click-through on recommendations based only on simplifying things was a big lesson learned, the biggest was without a doubt that “everything matters”. Ideas and hypotheses are a good starting point, but until proven they are just that: hypotheses.
Now, getting people to use our tools is only a first step in having impact. When it comes to recommendations, the next is having relevant ones. How do we make sure that they are? Well, we will test that too.
We tend to talk a lot about consumer protection in the gaming industry. It has become a vital part, and a bit of a buzz in business since a number of online markets have matured and regulatory bodies are challenging the industry into more preventive online actions against problematic gambling.
Therefore there is an urgent need to understand players’ online behavior. Not only for creating a perfect gaming experience: but in the case of consumer protection. But yet, there is still no consistency in what consumer protection really means and the question of “how we protect vulnerable players” has still not been answered. And meanwhile as we discuss all off this, we seem to miss the target.
The information every player provides to us could give us the answer. This article will argue that if we actually value consumer protection, not only as an abstract concept that we nod at agreeably during meetings – we should make use of information available: player data that is understood from a risk perspective.
Identification of high risk gambling in player data
A lot of data is being generated every minute of the day when players gamble both online and within land-based facilities like Casinos or eGaming machines. Purposely designed behavioral tracking solutions can identify patterns of play in gambling data, and with current technology, combined with understandings of problematic gambling; this can be utilized for proactive consumer protection.
Many players, with real life problem gambling stories, express that they have experienced “an escalation of their behavior” and before they knew what was happening: they were placing increased bets, and losing more and more money. By identifying these risk factors in player data – Operators get a new dimension in “knowing your customer”.
Player data holds a lot of information, such as age, gender, favorite game etc. But player data also holds descriptions of a player’s behavior. Looking at data from a risk perspective means to identify possible negative behaviors or risk factors, such as;
Start playing more often
For longer sessions
Constantly changing planned spending limits
These are a few examples that relate to user behavior rather than user information. With a risk analysis, it is possible to make players aware of changes in actual behavior.
This information provides direction for effective responsible gambling initiatives at an early stage, preventing problematic gambling instead of treating a problematic gambler. The risk analysis helps segment the player population into “low risk”, “increased risk” or “high risk” – leaving Operators with information for unique opportunities like customized responsible gambling communications.
How to understand data
Even if we have spent time on data analyses and even when players with risky gambling behavior are identified – it’s still tricky to answer the question “how can we protect vulnerable players?”
Data describes what players do, how they behave. But not really what they need.
One way to understand it and knowing what to do with data is to humanize and bring these numbers to life. For example: Wilma is a 45-year-old woman who likes gambling, especially online bingo. For the past six months she has gambled at a high-risk level, with few gambling-free days. Late nights with bingo, long sessions with lottery tickets after lottery tickets. She finds herself in a loop of wagering more and continuing to gamble, with higher stakes, even after she just lost.
This was not an ideal situation for Wilma, simply because she couldn’t afford it and lately her risk data indicates that she is trying to cut down on her gambling. For example, she is setting strict limits for her gambling that she has managed to keep within.
Should the Operator take any actions? Well, since Wilma previously has been on a high-risk journey, one thing that she does not need is to receive promotions, bonuses and commercials from her gaming company. This is were the operator can differentiate an out-going customer to one that just wants to control their gambling habits.
With customized communications, it could also be wise to inform Wilma, close to play, if her gambling sessions seem to be escalating again.
Why is this all meaningful?
By rethinking the way Operators use data and understand players, they can create meaningful communications that influence and engage the players. By taking the player’s risk level into consideration when communicating with player Operators can better focus on the user’s needs.
Knowing the player’s risk level is valuable through the whole chain of the gambling industry: from game design, marketing and user experience to management and business development all the way to customer support – and the player.
Simply, through understanding risk we avoid “one-size fits all” solutions and then we add true value to the concept of consumer protection. Because the point is that the answer to “how can we protect vulnerable players?” is that it varies according to each player’s risk behavior.
The Norwegian state owned lottery Norsk Tipping has now upgraded the responsible gambling tool Playscan into its latest version: Playscan 4.2. And they are making it mandatory for all their players. Not far after, Svenska Spel, the Swedish state owned lottery, made the same decision.
Players want responsible gambling tools that are easy to use and integrated in their overall gambling experience. That was the starting point for both Norsk Tipping and Svenska Spel.
Bjørn Helge Hoffmann, Chief Adviser Responsible Gaming at Norsk Tipping explains:
– By upgrading to Playscan 4 we are focused to make Playscan into a service for all, i.e. making Playscan mandatory to all our players. With this, our players are offered integrated communications in regards to changes in their gambling habits as part of their overall gaming experience.
Zenita Strandänger, CSR Manager at Svenska Spel, says that it is important for Svenska Spel to assist their players into making informed and responsible decisions about their gambling. She says:
– The tool promotes responsible gambling behaviors and it plays an important role in our overall consumer protection strategy. Making Playscan to a service for all players is simply a natural next step for us.
– We are very happy that these two Operators now is communicating with all their players that are showing signs of increased risk. That is great news for players and for our continued efforts in consumer protection, says Andreas Holmström, CEO of Playscan AB.
What a gambling operator should do when implementing responsible gambling
01.Educate all employees about the importance of responsible gambling. That means all the way from executives to your customer service team. Probably the most important thing to do to get acceptance for responsible gambling.
02. Train and educate retailers about the importance of responsible gambling. Retailers meet players all day long. Don’t underestimate their impact on your overall responsible gambling operations.
03. Get behavioural insights. Use your gambling data to understand the risk level of your customer. And intervene at the right time to minimize risk of harm and to secure sustainable revenue.
04. Customize communication to players needs. Take a critical look at how your gambling site is designed: present your tools and write your responsible gambling information in a way so your players can easily find and use them.
05. Talking about being a responsible gaming provider doesn’t make you one. It requires commitment and actions.
What do you know about your online player? With anonymous players, customer data is an important factor when making strategic business decisions with limited information. However, big data often becomes a faceless collection of information, rather than a true picture of the players’ wants and needs. One still needs to know how to interpret data and how to combine it with other sources of information.
User Personas brings together big data with qualitative user research such as interviews, field studies and observations to gain an overall picture of a user, their needs, goals and motivation. It also fills the gap between what players claim to act upon compared to their measured actions, which in the context of gambling often differs. Combined with big data, User Personas give the answers to three important questions: what are the main target groups, which target groups should be focused on to make the most impact, and how should communications be designed towards those target groups?
User research shows that players are concerned about keeping their gambling under control. An important aid for that is to let the player know how much time and money he or she spends on gambling. Playscan’s new feature will help players keep track of their spending by presenting charts on actual consumption of time and money.
Players can view their results, time spent, and monetary transactions on gambling and directly see patterns and trends. This allows them to get an aggregated view of their habits, and the opportunity to make informed choices about their gambling.
The feature is integrated into Playscan but can also be placed outside of the Playscan interface, as an add-on.
– Transparency is the absolute foundation in responsible gambling. Players ask for this information time and again, and it is our obligation to answer. I am pleased to have this feature in Playscan, and I’m thrilled for the positive response we’ve had from operators, says Henrik Hallberg, CTO Playscan AB.
Summary: Shortening the 16 statement Self Test within Playscan yields negligible improvement in completion rates. The length of the test is not a problem; players either drop off during the first couple of questions or complete the test.
A recurring concern about Playscan has been that 16 statements to consider in the Self Test may be too many. The player may grow impatient and abort the test, especially since the questions themselves can be sensitive and draining. We investigated whether a shorter introductory test with “gate questions” would increase the completion rate of tests.
When a player clicks into the Self Test, an introductory text is displayed. Here, the player is encouraged to consider all gambling, at all gambling sites, during the past three months. The player is then asked to consider 16 statements, one at a time.
To investigate the usefulness of gate questions, the results from the Self Tests at Svenska Spel between 2014-07-04 and 2014-10-14 were analyzed. Statistics of these are presented below, showing the completion and drop-off rates.
Looking at the numbers, the completion rate is quite satisfactory; in particular 80% web completion. This high number is likely due to the curiosity that brought the player to Playscan in the first place, and the promise of self-assessment at the end of the process. Self tests in general tend to have a higher completion rate than surveys thanks to the intrinsic motivation behind doing them.
The majority of the players who drop off do so at the first question. We also see a difference between channels with a 10% drop-off rate on web and 23% on mobile. The higher drop-off on mobile is hardly surprising, given the users’ attention span in the mobile context.
Only 10% of the started tests are dropped between question 2 and 16, regardless of channel. Interesting to note is that the drop-off rate declines as the test continues.
This leaves us with a clear answer to the question of gate questions. We would have yielded only 4% more completed tests if the test consisted of four statements. This number is hardly worth chasing at the cost of the players spending less time contemplating their gambling habits or missing out on the nuances that the full 16 statements bring.
The research done at Playscan is not academically focused, but aimed at practical application.
We are pragmatists, knee deep in data to explore. Our mission is to help prevent problem gambling rather than to study it, so we spend our time chasing preventive effect wherever we sense it.
We value agility and adaptation.
Where the territory is uncharted, our guiding light is curiosity and making a difference. Our data is local. We sometimes see wildly varying player behavior between operators, not necessarily because the players are different, but because contexts and presentations are. We believe that the research community has lots to learn about the importance of things like wording and design, and what we say will often be framed to show this. Our findings reflect the everyday player experience. This is neither universal nor static. It can change and, more importantly, can be changed.
At the same time, we have the deepest respect for formal research and academics. We welcome critique of our findings, and hope that others find inspiration and ideas to bring into the academic world. We are happy to help, and love to exchange experience and ideas. Give us a call if you would like to help out!
Playscan 3 helps at-risk players to reduce their spending on gambling.
A previous evaluation determined that players found Playscan to be a useful tool (Griffiths, Wood & Parke, 2009), but a systematic investigation of whether the tool influences players’ gambling behaviours had yet to be conducted. To address this gap we, Dr Richard Wood from GamRes Limited, Canada and Dr Michael Wohl from Carleton University, Canada, undertook an independent evaluation study the previous version, Playscan 3.
Specifically, we set out to empirically test the hypothesis that ‘The gambling behavior of players who use Playscan, will show a significant observable change, following the presentation of a negative change in risk category (i.e. Green to Yellow or Yellow to Red). In other words, we tested the idea that using Playscan can help players maintain, or return to, less risky patterns of play.
How was the study conducted?
Player data was examined for 1558 Swedish Internet players (n = 1388 male; n = 170 female). More males were present in the sample due to the data being drawn from a population that had a predominance of online poker players. Poker is a game that has a higher proportion of male versus female players. Six hundred and ninety four Playscan subscribers were compared to the same number of non-Playscan subscribers. The two groups of players were matched in terms of age, gender, gambling intensity, types of games played and current Playscan risk rating.
All players in the study were rated by Playscan, but only Playscan subscribers received feedback about their playing behaviour. This meant that everything else being equal, any changes in behaviour following feedback from Playscan would suggest that it was having an impact.
What did the evaluation study conclude?
It was found that Playscan subscribers who were informed that their rating was ‘Yellow’ (at-risk for gambling problems) showed a significant reduction in the amount of money deposited and wagered, compared to those players who did not use Playscan. This reduction in spending for at-risk players, was seen one week after enrolment with Playscan and was also evident 24 weeks after enrolment.
Based on the results, Wood and Wohl concluded that there is evidence to suggest Playscan is particularly helpful for Yellow players (those who show signs of risky play). That is, the feedback provided by Playscan, to those who show signs of risky play, was shown to reduce their levels of spending on gambling games tracked by Playscan. As such, Playscan appears to have responsible gambling utility – at least for those who are most at-risk for developing problematic patterns of play. Importantly, Red players (those who show signs of problematic play) enrolled in Playscan also reduced their expenditure on play, but so did Red players not enrolled in Playscan.
One explanation for this is that Red players, in both groups, may be more aware of a need to reduce their spending on games, as their playing is more obviously risky. Nevertheless, Red players who were using Playscan would have benefitted additionally from being given information to help them seek out the treatment or support that they may have required.
By Svenska Spel introducing mandatory registered play earlier this year, Playscan was able to provide a higher level of understanding about their VLT (Video Lottery Terminal) players. Players who gamble on a VLT machine in Sweden will now be offered a way to keep track of their gambling habits.
– We are very happy to now have Playscan linked to our VLT’s. The tool creates awareness and informs the player about their gambling habits. Also, internally this will improve our overall responsible gambling initiatives, says Zenita Strandänger, CSR-manager Svenska Spel.
With Playscan, Svenska Spel will be able to provide players with a risk analysis based on their player behavior. The player can easily access their Playscan risk analysis through both web and mobile.
– This will provide Svenska Spel with more statistical information for better decision-making, on top of state of the art player protection says Andreas Holmström, CEO Playscan.
Technical innovation is understood as bringing something new to the market and our minds are set to believe that there is a “technological fix” for every problem. Making new cars can solve problems with pollution; health problems can be solved with new medicine. Even problems with loneliness can be solved through online dating sites.
People ask each other constantly, “what is the latest thing?” Well, nowadays we talk a lot about sustainable innovations. For example, we have been faced with the reality that cars have a negative impact on our environment and we have set out on a mission to create new cars that don’t cause pollution problem. Yet, the question might not be how technology can help us with “quick fixes”. By using an electric car instead of a petrol-powered car, we don’t really change our behaviour or our way of thinking, do we? True innovation would be to re-think transportation in general.
The answer to the headline question is therefor: it already has. With current technical advances and innovations, responsible gambling is now making an impact on the user experience. Today, player tracking is being used as a communication portal that communicates with players through a risk perspective. For the responsible gaming provider this is ground breaking technology, because with player tracking, they have the means to create a sustainable gambling population – however, it is how we usethe technology that decides how well we will succeed.
The technical advances of responsible gambling already made must be systematically integrated in the mind-set of an Operator; today it is not an aspect of every decision, every move or every marketing strategy. The changing nature of responsible gambling and player tracking solutions is about how it now must work its way into being a natural part of the “customer experience” (which the industry tells us is the most important competitive differentiator) and produce insights for the Operator.
The challenge ahead is to find out how a gaming provider can engage the next generation of players without creating a new group of problematic gamblers.
The key to success is to focus on what players respond to
You need to get to know your players in order to figure out their needs. This is an old but not out-dated truth. With responsibility in mind, the knowledge of how your players behave could create a conflict between different sectors within the organisation. The tech team is often set out to gather Big Data and when the data has been contextualized into information, the obvious question for the marketing team is – “shouldn’t we try to use the information we have about our players to market our products better?”. The CSR department might instead scratch their heads and ask what should we do with these high-risk players we have identified?
The possible conflict between profit and responsibility does not benefit the concept of responsible gambling. It is necessary that the different departments within the organisation work together.
Relate the findings to the real world
Knowledge from different fields is needed when Big Data is interpreted. The information must be related to theories about problematic gambling, gambling addiction but also marketing principles, game design and customer support – if it is to have any meaning.
By mapping out the user journeys of your increased risk players, you would know where your responsible gambling efforts seem to have the best effect. For example, maybe there should be a limit on the amount of online scratch-tickets available to some players? Maybe some players shouldn’t be exposed to commercials for high-risk games at all?
It is not only about changing risky gambling behaviour – it is about changing the mind-set of a whole industry
There is an increasing need for institutionalised sustainable innovation within the gambling industry, but despite the many technical innovations developed in the field of responsible gambling, there are limits to what we can expect from any digital technology. After all, there are still real humans behind it. It is not only about using responsible gambling technology; it is about interpretation, cooperation and actions. It is about how you use it.
Can responsibility cut it in the tech world? Let us rephrase the first answer into: yes, if we let it. The determining factor of survival in the long-term depends on how successful we are in handling the issues of responsibility and how well we relate the technology to the real word.
Due to good first page exposure and a marketing campaign on the Operators website we saw an increase in the player activity during the beginning of June. We experienced a jump in activations (the amount of visitors was tripled compared with last year). A lot of non-risk players paid attention to Playscan and activated the tool. The novelty value didn’t scare them off – the tool kept most of the new activations.
The biggest change between Playscan 4 and previous versions is the players’ own perception of how well the Playscan risk analysis harmonizes with their own believes. The main positive movement of perception is with the increased risk players. 60% of the increased risk players agree with their analysis, something we find very exciting.
The information is useful
With Playscan 4 we have, when communicating with players, added informative texts such as “10 gambling commandments” and “What is gambling addiction?”. 8 out of 10 users appreciate these texts and find them useful.
More completed Self Tests
82% more completed Self Tests, compared with previous 75%. Both these numbers are high and indicate that people don’t mind answering questions about their gambling habits.
Increased risk players read informative texts
When a player has read their risk analysis they are given a recommendation based on their risk level. Simply because some tips are more relevant to a risk player than to a non-risk player.
So, what kind of recommendations is appreciated and most clicked? It turns out that increased risk players reads educating texts, such as “to have in mind while gambling”, while at risk players takes action by “setting up a budget”. The non-risk players are more likely to read general information on what problem gambling is and how it is manifested.